Construction and clinical application of a risk model based on N6-methyladenosine regulators for colorectal cancer

  • 0Oncology Department, The Sixth Affiliated Hospital of Jinan University, Dongguan, China.

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Summary

This summary is machine-generated.

This study developed a risk score based on N6-methyladenosine (m6A) regulators to predict colorectal cancer (CRC) prognosis. The model effectively differentiates high-risk patients with poor outcomes, aiding in CRC diagnosis and management.

Area Of Science

  • Oncology
  • Molecular Biology
  • Bioinformatics

Background

  • Colorectal cancer (CRC) is a prevalent malignancy in developed nations.
  • N6-methyladenosine (m6A) regulators play a role in CRC progression.
  • Establishing prognostic signatures is crucial for CRC management.

Purpose Of The Study

  • To develop a prognostic signature for colorectal cancer (CRC) based on m6A regulators.
  • To identify key m6A regulators and their association with CRC patient outcomes.
  • To explore potential therapeutic targets and immune infiltration in CRC.

Main Methods

  • Utilized bulk and single-cell RNA sequencing data from public databases (AC-ICAM, GSE33113, GSE146771).
  • Performed consensus clustering, Gene Set Enrichment Analysis (GSEA), and LASSO Cox regression to build a risk model.
  • Conducted in vitro assays (qPCR, wound healing, transwell) and analyzed immune cell infiltration and drug sensitivity.

Main Results

  • Identified three molecular subtypes of CRC based on nine m6A regulators.
  • Developed a RiskScore using METTL3, IGF2BP3, and YTHDC2, effectively classifying patients into high- and low-risk groups.
  • High-risk patients exhibited poorer prognosis, increased immune cell infiltration, and activated inflammatory pathways. Inhibition of METTL3 or IGF2BP3 reduced CRC cell invasion and migration.
  • A nomogram was developed for clinical application, and eight potential drugs were identified.

Conclusions

  • The m6A regulator-based RiskScore is a critical predictor of colorectal cancer (CRC) development and patient prognosis.
  • This model can significantly aid in the diagnosis and clinical management of CRC patients.
  • Findings provide insights into the role of m6A modification in CRC and potential therapeutic strategies.